Smart interactions for the quantified self

Abstract

The Quantified Self is a movement for collecting personal data with the goal of providing possibilities for new insights through reflecting on own relevant data, with applications in areas such as physical exercise, food, and health. When collecting personal data, difficulties may arise, such as information from different sources which cannot easily be combined, closed access to information sources, inflexible tooling for producing desired quantifications, varying precision of data used for producing quantifications, and a lack of control over data sharing for supporting relevant comparisons with others. In this paper, we introduce the concept of smart interactions, backed by linked data, as a means of introducing the QS through smart and personal learning environments, both for reducing the associated difficulties and further empowering the QS.